Solving multi-mode resource-constrained project scheduling problem using two multi objective evolutionary algorithms

Abstract

The aim of this research is to present a new mathematical model for a multi-mode resource-constrained project scheduling problem (MRCPSP) with discounted cash flows. The objective is to minimize the project makespan and maximize the net present value (NPV), simultaneously, which are the two common objectives of this problem in the literature. Two evolutionary algorithms, NSGA-II and MOPSO are applied to find the set of Pareto solutions for this bi-objective scheduling problem. Furthermore, a new policy is proposed to have feasible solutions for both algorithms. To show the superiority and applicability of the algorithms, different metrics are applied and the graphical comparisons are also considered. Finally, the computational results illustrate the superior performance of the NSGA-II algorithm with regard to the proposed metrics.   Key words: Resource-constraint, multi-mode project scheduling, net present value, makespan, evolutionary multi objective optimization.